Recent advancements in the field of computer vision have led to development of various methods and techniques for visual tracking of objects over a period of time by use of a tracker, such as an imaging device. Typically, the tracker estimates the trajectory of an object in an image plane, as the object moves around in a scene. In other words, the tracker assigns consistent labels to the objects and accordingly, attempts to locate the same object in subsequent frames of a video clip.
Currently, various techniques, such as template tracking techniques, are utilized for object tracking in video content. Generally, the template tracking techniques extract object features from an image patch of an object via “spatially sensitive” features, such as histogram of oriented gradients (HOG). During tracking, the template tracking techniques register the image patch of the object with next instance of the object in the next frame, via one of more difference metrics, such as Sum of Square Difference (SSD) or Normalized Cross Correlation (NCC). However, in an event that the object is associated with occlusions and non-rigid deformations, the template tracking technique may provide inaccurate tracking results as the tracking gets drifted from the original location of the object. Thus, an advanced and robust tracking technique may be required to accurately track such objects that are associated with deformations and occlusions.
Further limitations and disadvantages of conventional and traditional approaches will become apparent to one of skill in the art, through comparison of described systems with some aspects of the present disclosure, as set forth in the remainder of the present application and with reference to the drawings.